Pharmacogenetics of dolutegravir plasma exposure among Southern Africans living with HIV

Background Dolutegravir is a component of preferred antiretroviral therapy (ART) regimens. We characterised the pharmacogenetics of dolutegravir exposure following ART initiation in the ADVANCE trial in South Africa. Methods Genome-wide genotyping followed by imputation was performed. We developed a population pharmacokinetic model for dolutegravir using non-linear mixed-effects modelling. Linear regression models examined associations with unexplained variability in dolutegravir area under the concentration-time curve (AUCVAR). Results Genetic associations were evaluable in 284 individuals. Of nine polymorphisms previously associated with dolutegravir pharmacokinetics, the lowest P-value with AUCVAR was UGT1A1 rs887829 (P = 1.8 x 10-4), which was also associated with log10 bilirubin (P = 8.6 x 10-13). After adjusting for rs887829, AUCvar was independently associated with rs28899168 in the UGT1A locus (P = 0.02), as were bilirubin concentrations (P = 7.7 x 10-8). In the population pharmacokinetic model, rs887829 T/T and C/T were associated with 25.9% and 10.8% decreases in dolutegravir clearance, respectively, compared to C/C. The lowest P-value for AUCVAR genome-wide was CAMKMT rs343942 (P = 2.4 x 10-7). Conclusions In South Africa, rs887829 and rs28899168 in the UGT1A locus were independently associated with dolutegravir AUCVAR. The novel rs28899168 association warrants replication. This study enhances understanding of dolutegravir pharmacogenetics in Africa.


Introduction
Sub-Saharan Africa has the highest prevalence of HIV-1 infection worldwide (1). Dolutegravir is an HIV-1 integrase strand transfer inhibitor with a favourable safety profile and high barrier to viral resistance (2). The World Health Organization recommends dolutegravir with tenofovir and lamivudine as a preferred regimen for ART-naïve patients, and dolutegravir-based ART as a switch option when failing ART or transitioning for programmatic reasons (3). In South Africa, preferred initial regimens include dolutegravir, together with either tenofovir and emtricitabine, or abacavir with lamivudine (4).
Studies of ART pharmacogenetics may guide ART optimization in different populations. Africa has the world's greatest genetic diversity (7), but data are limited regarding dolutegravir pharmacogenetics in Africa. We characterized genetic associations with dolutegravir exposure among ART-naïve African participants in the ADVANCE study (8).

Study population
The ADVANCE study in South Africa was a phase 3 clinical trial (clinicaltrial.gov NCT03122262) in which 1,053 HIV-positive, ART-naïve participants were randomly assigned to one of three treatment arms: 1) dolutegravir, tenofovir alafenamide (TAF) and emtricitabine; 2) dolutegravir, tenofovir disoproxil fumarate (TDF) and emtricitabine; or 3) efavirenz, TDF and emtricitabine (8). The present study included dolutegravir arm participants who consented to genetic testing.
were taken pre-dose and at 1, 2, 4, 6, 8, and 24 hours post-dose. Doses preceding intense sampling were observed following a standard meal. For all other individuals, sparse pharmacokinetic sampling (at least one sample) was performed at either week 48 or 96.
Dolutegravir was quantified with a validated assay developed at the Division of Clinical Pharmacology, University of Cape Town. Samples were processed with a liquid-liquid extraction method using dolutegravir-d4 as an internal standard, followed by high performance liquid chromatography with tandem mass spectrometry detection (LC/MS/MS) using an AB SCIEX API 4000 instrument. Analyte and internal standard were monitored at mass transitions of the protonated precursor ions m/z 420.1 and m/z 424.2 to the product ions m/z 277.2 and m/z 279.1, respectively. The calibration curve fitted a quadratic regression over the range 0.030 to 10.0 μg/mL. Combined accuracy and precision statistics of quality control samples during validation were between 103.5% and 106.0%, and 4.6% and 6.1%, respectively. The laboratory participated in the Clinical Pharmacology Quality Assurance external quality control program under a contract with the Division of AIDS of the National Institute of Allergy and Infectious Diseases, through which this assay was approved.

Genetic polymorphisms
Whole blood was collected from consenting participants, and DNA extracted as described elsewhere (9). Samples were labelled with coded identifiers. Stored DNA was genotyped using the Illumina Infinium Multi-Ethnic Global BeadChip (MEGA EX ) at Vanderbilt Technologies for Advanced Genomics (VANTAGE). Post-genotype quality control included sex checks, call rates by marker and sample, identity by descent (IDB) plots, assessment for batch effects, concordance between duplicate samples, and HapMap controls.
Quality control steps were performed using PLINK version 1.9 (10). Genotyping efficiency per participant was > 95% for all samples. After quality control, data were imputed using the TOPMed reference panel after transforming to genome build 38 using liftOver and stratification by chromosome to parallelize the imputation process (11). We excluded imputed polymorphisms with imputation scores < 0.3, genotyping call rates < 95%, minor allele frequency (MAF) < 0.05, or Hardy-Weinberg Equilibrium P-values < 1.0 x10 -8 . Linkage disequilibrium (LD) r 2 values were determined using PLINK.

Population pharmacokinetic modelling (without genetics)
Concentration-time data were analysed by non-linear mixed-effects modelling with NONMEM (v7.5.0, ICON Development Solutions, Ellicott City, MD, USA). First-order conditional estimation with eta-epsilon interaction were used to fit models to the observations. Pearl-speaks-NONMEM (PsN) v4.7.0, Pirana v2.9.7, and R v3.6.1 were used for model automation and tracking, and to create and visualize model diagnostics. We tested various structural models to describe the pharmacokinetics of dolutegravir including oneand two-compartment disposition models, first-order elimination and absorption, with or without absorption lag time, and transit compartments (12). We included between-individual and between-occasion random effects on the model parameters with an assumption of a log-normal distribution. A combined (additive and proportional) error model was used to describe the residual unexplained variability, with the additive component of the error constrained to be at least 20% of the lower limit of quantification.
Throughout the pharmacokinetic analysis, model development was guided by inspection of diagnostic plots, including visual predictive checks (VPC), and decreases in the NONMEM objective function value (OFV), which were assumed to follow a chi-square distribution. To discriminate between nested models, a decrease in OFV of -3.84 was equivalent to model improvement at P < 0.05. To adjust for the effect of body size on disposition parameters, we added allometric scaling to the model. We tested total body weight and fat-free mass (FFM) with the allometric exponents for clearance and volume parameters fixed to 0.75 and 1, respectively (13). After the inclusion of allometric scaling, we investigated effects of the following covariates: sex, age, and TAF-versus TDF-containing ART. Covariates were assessed by stepwise inclusion followed by backward elimination and were retained at a significance level of 0.01. To evaluate the robustness of parameter estimates in the final model, we ran a sampling-importance resampling exercise and generated 95% confidence intervals (CI).

Unexplained variability to be regressed against genetics
The final model was used to generate individual steady-state estimates of area under the concentration-time curve (AUC 0-24h ) and unexplained variability in AUC 0-24h (AUC VAR ) for individuals with at least one pharmacokinetic sample. Individual estimates of all model parameters were obtained from the final model by a post-hoc Bayes estimation method, considering an individual's pharmacokinetic data and characteristics (i.e., FFM). Individual estimates of AUC 0-24h were obtained using the formula AUC 0-24h = F i x Dose i /CL i , where Dose represents the actual dose given to each individual and CL i and F i represent individual estimates of clearance and bioavailability, respectively.

Genetic association analyses
The outcome of primary interest was AUC VAR , and secondarily unexplained variability in dolutegravir clearance (CL BSV ). Multivariable linear regression models characterised associations with genetic polymorphisms. To adjust for genetic ancestry, we estimated continuous axes of ancestry incorporating the intersection of common autosomal genotypes using EIGENSTRAT (14). Principal components scree plots were used to assess whether components included in analyses were informative; based on this, two principal components were sufficient. Other than principal components, additional covariates were not included in association analyses because they were accounted for in the population pharmacokinetic model. We report regression coefficients (b) for additive associations with polymorphisms, where positive b values indicate an association with increased AUC VAR . The Bonferroni method was used to determine significance thresholds, with 0.05 divided by the number of polymorphisms tested in targeted polymorphism and gene analyses, and P < 5.0 x10 -8 for genome-wide analyses.
We also selected rs887829 which is in strong linkage with rs8175347. Beyond these polymorphisms, we then stepwise prioritized sets of polymorphisms to interrogate so as to decrease the burden of multiple testing. We reasoned that polymorphisms previously and strongly associated with at least one drug-related phenotype, or that have been significantly genome-wide associated with any trait, are most likely to be true associations. We used as references the Pharmacogenomics Knowledge Base (PharmGKB, accessed 13 July 2021) (15) and NHGRI-EBI GWAS Catalog (accessed 19 January 2021) (16). In PharmGKB, 173 polymorphisms were previously associated with at least one drug-related phenotype (pharmacokinetics, efficacy, or toxicity) with levels of evidence of 1 (preponderance of evidence shows an association, replicated in multiple cohorts, and preferably with strong effect size) or 2 (moderate evidence of association, replicated but some studies may not show statistical significance, or with small effect size). In the GWAS Catalog, 89,716 polymorphisms were previously associated with any trait at P < 5.0 x10 -8 in at least one study.
We prioritized polymorphisms common to both PharmGKB and the GWAS Catalog, considering these to have the most robust evidence for true associations. We secondarily explored all polymorphisms from PharmGKB and the GWAS Catalog (based on criteria described above), and all polymorphisms in our imputed genome-wide genotype data.
As a positive control, we tested for associations between UGT1A locus polymorphisms and screening bilirubin concentrations. Bilirubin is conjugated by UGT1A1, and there are strong associations between UGT1A1 polymorphisms (e.g., rs887829) and bilirubin concentrations (17).

Population pharmacokinetic modelling with genetic information
Based on results of our genetic association analyses, we assessed effects of selected polymorphisms on dolutegravir clearance, on all available pharmacokinetic data (intensive and sparse samples). In addition to participants with genotype data, both intensive and sparse pharmacokinetic data was available from other ADVANCE participants. For such individuals we assigned a phenotype using mixture modelling as described elsewhere (18).

Study population
Among 340 ADVANCE participants who consented for genetic analyses, 284 (84%) were successfully genotyped and had pharmacokinetic data. Participant disposition is presented in Figure 1. All participants were Black Africans and 62% were females. Study participant characteristics are shown in Table 1.

Dolutegravir population pharmacokinetics without genetics
For this model, data were available from 41 intensively sampled individuals who provided 276 dolutegravir concentrations (40 complete profiles, and 1 pre-dose sample from an individual for whom intravenous access difficulty precluded additional samples). Median (interquartile range) weight and age were 73.1 (67.2 -85.2) kg and 31 (29 -36) years, respectively. A two-compartment disposition model (ΔOFV=-47, P < 0.001 compared to one-compartment) with first-order elimination and transit compartments absorption (ΔOFV=-4.8, P = 0.028 compared to absorption lag) best described pharmacokinetics. Allometric scaling with FFM best described the effect of body size on disposition parameters and was applied to all clearance and volume parameters. We estimated clearance of 0.732 L/h, central volume of 12.2 L, and peripheral volume of 5.87 L for a typical individual with a 47 kg FFM and included between-subject variability on clearance and between-occasion variability on mean transit time (MTT), absorption rate constant, and bioavailability. Final parameter estimates, precision and the VPC shows that the model described the data adequately (Supplementary Data).

Genetic associations with dolutegravir pharmacokinetics
Seven of 12 polymorphisms previously associated with dolutegravir pharmacokinetics were present in our genetic data. Of the five not included, three (rs4148323, rs8175347 and rs35599367) are very infrequent in African populations (MAF approximately 1% or less), and one was not genotyped (UGT1A1*28 rs8175347) but is in strong LD with rs887829 (19). Of the remaining seven polymorphisms, the lowest P-value for association with AUC VAR was UGT1A1 rs887829 (β = 0.14, P = 1.8 x 10 -4 ) with a MAF of 0.41 (Table   2). This withstood correction for multiple testing (cut-off P < 5.6 x 10 -3 ) and was also most strongly associated with CL BSV (β = -0.09, P = 8.4 x 10 -6 ) (Supplementary Data). Association of the other six polymorphisms with CL BSV were consistent with those for AUC VAR (data not shown). This was expected, since AUC is derived from CL (AUC (0-24) = F i x Dose i /CL i ,) and these parameters were highly correlated (Spearman r 2 = -0.96).
To determine whether rs6736508 or other UGT1A locus polymorphism were associated with AUC VAR independent of rs887829, we repeated the above analyses after adjusting for rs887829, which should strengthen any true independent association. In this analysis, rs6736508 became 2-log less significant (β= 0.13, P = 4.2 x 10 -3 ), and no longer withstand correction for multiple testing, indicating that its association was largely if not entirely dependent on rs887829. Results for CL BSV were consistent with results for AUC VAR (data not shown). To guide next steps, we used log 10 bilirubin as a biomarker to identify additional variants that may affect UGT1A1 activity independent of rs887829. After adjusting for rs887829, a UGT1A locus polymorphism rs28899168 was independently associated with lower log 10 bilirubin concentrations (β = -0.11, P = 7.7 x 10 -8 ). This polymorphism was also independently associated with lower AUC VAR (β = -0.12, P = 0.02). P-values for UGT1A locus polymorphisms with AUC VAR and CL BSV after adjusting for rs887829 are presented in Supplementary Data.
The 10 lowest P-values for AUC VAR and for log 10 bilirubin concentrations are presented in Table 2. Results for CL BSV were consistent with results for AUC VAR (data not shown). For CL BSV, the lowest P-value was LOC105377607 rs201393786 on chromosome 4 (β = 0.10, P = 2.6 x 10 -7 ) (Supplementary Data). As we did for UGT1A locus polymorphisms, we characterized associations genome-wide after adjusting for rs887829. In these analyses, the lowest P-value for dolutegravir AUC VAR was ADGRE4P rs7256367 (β = 0.20, P = 2.6 x 10 -7 ), which was also the lowest P-value for CL BSV (β = -0.11, P = 2.3 x 10 -7 ), and did not withstand correction for multiple testing. The 10 lowest P-values for AUC VAR after adjusting for rs887829 are in Supplementary Data. We next considered 89,716 polymorphisms previously associated with any trait in the GWAS Catalog. In these analyses, the lowest P-value for AUC VAR was CAMKMT rs343968 (β = 0.33, P = 2.8 x 10 -6 ). The 10 lowest P-values for association with AUC VAR are presented in Table 3. PharmGKB and GWAS Catalog polymorphisms included in our analyses are provided in Supplementary Data. Results for CL BSV were consistent with results for AUC VAR (data not shown), with the lowest the lowest P-value being rs4148325 in the UGT1A locus (β = -0.09, P = 5.0 x 10 -6 ), which is in strong LD with rs887829 (r 2 = 0.99).

Including genotype in the population pharmacokinetic model
Among the 41 intensively sampled individuals, 26 (8 with C/C, 10 with C/T, 8 with C/T) had UGT1A1 rs887829 genotype information and when this was tested on dolutegravir clearance, there was a graded trend towards reduced clearance for C/T and T/T individuals of borderline significance. However, when we fitted a mixture model to all available pharmacokinetic data (intensive and sparse samples) there was a significant and graded effect of UGT1A1 rs887829 genotype on dolutegravir clearance (ΔOFV= -24.7, P < 0.00001 compared to no genotype). We estimated a clearance of 0.78 L/h for C/C, with a 10.8% and 25.9% decrease in clearance for C/T, and T/T, respectively. This included 472 individuals (188 not genotyped) who provided 742 concentrations. Simulations performed using the final model and highlighted in Figure 4 show that dolutegravir trough concentrations are highest with T/T genotypes. A VPC and a schematic of the model are in Supplementary Data.
Testing the effect of rs6736508 on dolutegravir clearance within a model that already included rs887829 only improved the model by -5.73 points (P = 0.057) and therefore, rs6736508 was not retained in the model. On the other hand, testing the effect of rs28899168 within a model that already included rs887829 improved the model by -7.42 points (P = 0.0244). However, this was not significant at the backward elimination step where we used a threshold of P < 0.01 and therefore, rs28899168 was not retained in the final model.

Discussion
We characterised genetic associations with between-individual variability in dolutegravir exposure among participants in the ADVANCE study in South Africa. Among polymorphisms previously associated with plasma dolutegravir exposure (20)(21)(22)(23), the UGT1A1 rs887829 T allele was associated with greater AUC VAR (P = 1.8 x 10 -4 ). This allele is known to be in strong linkage with the Gilbert trait decreased expression allele, UGT1A1*28, a promoter TA n dinucleotide (19). Our finding supports previously reports associating UGT1A1*28 with dolutegravir concentrations (20,21,23). In prior genome-wide association studies of bilirubin concentrations, rs887829 was most strongly and consistently associated (17,24). When included in the population pharmacokinetic model, rs887829 C/T and T/T genotypes were associated with 10.8% and 25.9% decreases in dolutegravir clearance, respectively, and thus higher exposures compared to C/C individuals.
To identify novel UGT1A locus associations with dolutegravir exposure we used screening bilirubin concentration as a biomarker for UGT1A1 activity. After controlling for rs887829, a second UGT1A locus polymorphism, rs28899168 (intronic in UGT1A8, UGT1A9, and UGT1A10) was independently associated with log 10 bilirubin concentrations (P = 7.7 x 10 -8 , below the Bonferroni P-value cut-off of 5.9 x 10 -5 ), suggesting that rs28899168 was associated with increased UGT1A1 expression or activity independent of rs887829 (albeit with a P-value 5-log greater than that for rs887829). After adjusting for rs887829, rs28899168 was also independently associated with lower dolutegravir AUC VAR (P = 0.02). Although the P-value for rs28899168 did not withstand correction for multiple comparisons, it is likely true given its independent association with bilirubin. This polymorphism has not been previously associated with dolutegravir pharmacokinetics or bilirubin.
In genome-wide analyses for associations with AUC VAR , the lowest P-value was CAMKMT rs343942 (P = 2.4 x 10 -7 ), which has not been previously associated with dolutegravir pharmacokinetics. CAMKMT catalyses Lys-116 trimethylation in calmodulin (25), and other CAMKMT polymorphisms have been associated with anxiety risk (25,26). The second lowest P-value was MIR99AHG rs9980715 (P = 6.6 x 10 -7 ). MIR99AHG is a potential noncoding tumor suppressor gene in lung adenocarcinoma (27). These seem unlikely to represent true associations with dolutegravir pharmacokinetics.
Previous reports have associated UGT1A1*28 rs8175347 with dolutegravir pharmacokinetics. Using data from nine Phase I and II studies involving 89 participants of European-American or African-American descent, UGT1A1*28 was associated with a 32% decrease in dolutegravir oral clearance, a 46% increase in AUC, and a 32% increase in C max (20). Among 107 Japanese patients, UGT1A1*28 and UGT1A1*6 (rs4148323) were associated with increased dolutegravir concentrations (21). UGT1A1*6 is rare among Africans and Europeans but frequent among Asians. Using data from three Phase I and one Phase III clinical trials involving 93 Caucasian and Black African or Caribbean participants, UGT1A1*28 was associated with 28% increased dolutegravir plasma AUC 0-24h (23). The UGT1A1 rs887829 association in our study supports previous reports. Beyond UGT1A1, ABCG2 rs2231142 and NR1I2 rs2472677 in combination were suggested to be associated with increased dolutegravir C max , while no further associations were found in ABCG2 rs2231137, CYP3A4*22 rs35599367, CYP3A5*3 rs776746, and NR1I2 rs1523130 (23).
During HIV-1 treatment, plasma dolutegravir concentrations considerably exceed what is required to inhibit wild-type virus replication. Therefore, loss-of-function polymorphisms in UGT1A1 are unlikely to increase antiviral efficacy. However, lower plasma dolutegravir exposure with the UGT1A1 rs887829 C allele may be important in some situations, such as in patients receiving concomitant medications that increase dolutegravir clearance or decrease absorption, or in patients harbouring HIV-1 with reduced susceptibility to dolutegravir. Conversely, higher plasma dolutegravir concentrations associated with UGT1A1 rs887829 T alleles may increase the risk of intolerability, supported by a Japanese study of 107 patients which reported a greater incidence of selected grade 1 or 2 neuropsychiatric adverse events among individuals carrying UGT1A1*6 or UGT1A1*28 (P = 0.05).
Our study had limitations. Although sample size was modest, this was the largest pharmacogenetic study of dolutegravir to date. A larger sample size may have identified novel genome-wide significant associations. We could not replicate some polymorphisms that were very infrequent in Africans. We did not directly genotype UGT1A1*28. However, we selected UGT1A1 rs887829 which is in strong linkage disequilibrium with UGT1A1*28.
In summary, two UGT1A locus polymorphisms were independently associated with dolutegravir AUC VAR in a Black African population, one of which was expected (rs887829) and one of which was novel (rs28899168). The latter association should be replicated in other large cohorts. This study extends our understanding of dolutegravir pharmacogenetics in Africa, which is important given the widespread prescribing of dolutegravir in Africa.

Supplementary Material
Refer to Web version on PubMed Central for supplementary material.  Of 1,053 participants enrolled in the ADVANCE study, 284 who were randomized to dolutegravir-containing regimens and with available pharmacokinetic sampling data were evaluable for genetic associations. CWRES; conditional weighted residual, BLQ; below limit of quantification.       c Polymorphism rs887829 was in complete linkage with rs1976391 in our imputed genotype data, so gave identical results.